Multi-objective optimization has been increasingly applied in engineering where optimal decisions need to be made in the presence of trade-offs between two or more objectives. Minimizing the volume of shrinkage porosi...Multi-objective optimization has been increasingly applied in engineering where optimal decisions need to be made in the presence of trade-offs between two or more objectives. Minimizing the volume of shrinkage porosity, while reducing the secondary dendritic arm spacing of a wheel casting during low-pressure die casting(LPDC) process, was taken as an example of such problem. A commercial simulation software Pro CASTTM was applied to simulate the filling and solidification processes. Additionally, a program for integrating the optimization algorithm with numerical simulation was developed based on SiPESC. By setting pouring temperature and filling pressure as design variables, shrinkage porosity and secondary dendritic arm spacing as objective variables, the multi-objective optimization of minimum volume of shrinkage porosity and secondary dendritic arm spacing was achieved. The optimal combination of AZ91 D wheel casting was: pouring temperature 689 °C and filling pressure 6.5 kPa. The predicted values decreased from 4.1% to 2.1% for shrinkage porosity, and 88.5 μm to 81.2 μm for the secondary dendritic arm spacing. The optimal results proved the feasibility of the developed program in multi-objective optimization.展开更多
In this paper, we present an algorithm to solve the inequality constrained multi-objective programming (MP) by using a penalty function with objective parameters and constraint penalty parameter. First, the penalty fu...In this paper, we present an algorithm to solve the inequality constrained multi-objective programming (MP) by using a penalty function with objective parameters and constraint penalty parameter. First, the penalty function with objective parameters and constraint penalty parameter for MP and the corresponding unconstraint penalty optimization problem (UPOP) is defined. Under some conditions, a Pareto efficient solution (or a weakly-efficient solution) to UPOP is proved to be a Pareto efficient solution (or a weakly-efficient solution) to MP. The penalty function is proved to be exact under a stable condition. Then, we design an algorithm to solve MP and prove its convergence. Finally, numerical examples show that the algorithm may help decision makers to find a satisfactory solution to MP.展开更多
This paper presents a modified method to solve multi-objective nonlinear programming problems with fuzzy parameters in its objective functions and these fuzzy parameters are characterized by fuzzy numbers. The modifie...This paper presents a modified method to solve multi-objective nonlinear programming problems with fuzzy parameters in its objective functions and these fuzzy parameters are characterized by fuzzy numbers. The modified method is based on normalized trade-off weights. The obtained stability set corresponding to α-Pareto optimal solution, using our method, is investigated. Moreover, an algorithm for obtaining any subset of the parametric space which has the same corresponding α-Pareto optimal solution is presented. Finally, a numerical example to illustrate our method is also given.展开更多
To enhance the output torque and minimize the torque ripple of coaxial magnetic gear(CMG),a novel auxiliary flux modulator CMG with unequal magnetic poles is proposed.This design incorporates an inner rotor with an as...To enhance the output torque and minimize the torque ripple of coaxial magnetic gear(CMG),a novel auxiliary flux modulator CMG with unequal magnetic poles is proposed.This design incorporates an inner rotor with an asymmetric sector and a trapezoidal combined N-S pole structure,featuring Halbach arrays for the arrangement of permanent magnets(PMs).The outer rotor PMs adopt a Spoke-type configuration.To optimize the CMG for high output torque and low torque ripple,a sensitivity analysis is conducted to identify key size parameters that significantly influence the optimization objectives.Based on the sensitivity hierarchy of these parameters,a multi-objective optimization analysis is performed using a genetic algorithm(GA)to determine the optimal structural parameter values of the CMG.In addition,a coaxial magnetic gear(CMG)topology with 4 inner and 17 outer pole pairs is adopted,and the parametric model is established.Finally,the electromagnetic properties of the CMG are evaluated using the finite element method.The results indicate a remarkable reduction in torque ripple,specifically by 46.15%.展开更多
Enhancing the adaptability of Unmanned Aerial Vehicle(UAV)swarm control models to cope with different complex working scenarios is an important issue in this research field.To achieve this goal,control model with tuna...Enhancing the adaptability of Unmanned Aerial Vehicle(UAV)swarm control models to cope with different complex working scenarios is an important issue in this research field.To achieve this goal,control model with tunable parameters is a widely adopted approach.In this article,an improved UAV swarm control model with tunable parameters namely Multi-Objective O-Flocking(MO O-Flocking)is proposed.The MO O-Flocking model is a combination of a multi rule control system and a virtual-physical-law based control model with tunable parameters.To achieve multi-objective parameter tuning,a multi-objective parameter tuning method namely Improved Strength Pareto Evolutionary Algorithm 2(ISPEA2)is designed.Simulation experiment scenarios include six target orientation scenarios with different kinds of objectives.Experimental results show that both the ISPEA2 algorithm and MO O-Flocking control model have good performance in their experiment scenarios.展开更多
To investigate cutting performance in the helical milling of carbon fiber reinforced polymer(CFRP),experiments were conducted with unidirectional laminates.The results show that the influence of cutting parameters is ...To investigate cutting performance in the helical milling of carbon fiber reinforced polymer(CFRP),experiments were conducted with unidirectional laminates.The results show that the influence of cutting parameters is very significant in the helical milling process. The axial force increases with the increase of cutting speed, which is below 95 m/min; otherwise, the axial force decreases with the increase of cutting speed. The resultant force always increases when cutting speed increases; with the increase of tangential and axial feed rates, cutting forces increase gradually. In addition, damage rings can appear in certain regions of the entry edges; therefore, the relationship between machining performance(cutting forces and holemaking quality) and cutting parameters is established using the nonlinear fitting methodology. Thus, three cutting parameters in the helical milling of CFRP, under the steady state, are optimized based on the multi-objective genetic algorithm, including material removal rate and machining performance. Finally, experiments were carried out to prove the validity of optimized cutting parameters.展开更多
As the manufacturing industry is facing increasingly serious environmental problems, because of which carbon tax policies are being implemented, choosing the optimum cutting parameters during the machining process is ...As the manufacturing industry is facing increasingly serious environmental problems, because of which carbon tax policies are being implemented, choosing the optimum cutting parameters during the machining process is crucial for automobile panel dies in order to achieve synergistic minimization of the environment impact, product quality, and processing efficiency. This paper presents a processing task-based evaluation method to optimize the cutting parameters, considering the trade-off among carbon emissions, surface roughness, and processing time. Three objective models and their relationships with the cutting parameters were obtained through input–output, response surface, and theoretical analyses, respectively. Examples of cylindrical turning were applied to achieve a central composite design(CCD), and relative validation experiments were applied to evaluate the proposed method. The experiments were conducted on the CAK50135 di lathe cutting of AISI 1045 steel, and NSGA-Ⅱ was used to obtain the Pareto fronts of the three objectives. Based on the TOPSIS method, the Pareto solution set was ranked to find the optimal solution to evaluate and select the optimal cutting parameters. An S/N ratio analysis and contour plots were applied to analyze the influence of each decision variable on the optimization objective. Finally, the changing rules of a single factor for each objective were analyzed. The results demonstrate that the proposed method is effective in finding the trade-off among the three objectives and obtaining reasonable application ranges of the cutting parameters from Pareto fronts.展开更多
A geothermal demonstration exploitation area will be established in the Enhanced Geothermal System of the Qiabuqia field, Gonghe Basin, Qinghai–Xizang Plateau in China. Selection of operational parameters for geother...A geothermal demonstration exploitation area will be established in the Enhanced Geothermal System of the Qiabuqia field, Gonghe Basin, Qinghai–Xizang Plateau in China. Selection of operational parameters for geothermal field extraction is thus of great significance to realize the best production performance. A novel integrated method of finite element and multi-objective optimization has been employed to obtain the optimal scheme for thermal extraction from the Gonghe Basin. A thermal-hydraulic-mechanical coupling model(THM) is established to analyze the thermal performance. From this it has been found that there exists a contraction among different heat extraction indexes. Parametric study indicates that injection mass rate(Q_(in)) is the most sensitive parameter to the heat extraction, followed by well spacing(WS) and injection temperature(T_(in)). The least sensitive parameter is production pressure(p_(out)). The optimal combination of operational parameters acquired is such that(T_(in), p_(out), Q_(in), WS) equals(72.72°C, 30.56 MPa, 18.32 kg/s, 327.82 m). Results indicate that the maximum electrical power is 1.41 MW for the optimal case over 20 years. The thermal break has been relieved and the pressure difference reduced by 8 MPa compared with the base case. The optimal case would extract 50% more energy than that of a previous case and the outcome will provide a remarkable reference for the construction of Gonghe project.展开更多
To deal with the increasing demand for low-volume customization of the mechanical properties of cold-rolled products, a two-way control method based on mechanical property prediction and process parameter optimization...To deal with the increasing demand for low-volume customization of the mechanical properties of cold-rolled products, a two-way control method based on mechanical property prediction and process parameter optimization(PPO) has become an effective solution. Aiming at the multi-objective quality control problem of a company's cold-rolled products, based on industrial production data, we proposed a process parameter design and optimization method that combined multi-objective quality prediction and PPO. This method used the multi-output support vector regression(MSVR) method to simultaneously predict multiple quality indices. The MSVR prediction model was used as the effect verification model of the PPO results. It performed multi-process parameter collaborative design and realized the optimization of production process parameters for customized multi-objective quality requirements. The experimental results showed that, compared with the traditional single-objective quality prediction model based on support vector regression(SVR), the multi-objective prediction model could better take into account the coupling effect between process parameters and quality index, the MSVR model prediction accuracy was higher than that of the SVR, and the optimized process parameters were more capable and reflected the influence of metallurgical mechanism on the quality index,which were more in line with actual production process requirements.展开更多
This paper studies a time-variant multi-objective linear fractional transportation problem. In reality, transported goods should reach in destinations within a specific time. Considering the importance of time, a time...This paper studies a time-variant multi-objective linear fractional transportation problem. In reality, transported goods should reach in destinations within a specific time. Considering the importance of time, a time-variant multi-objective linear fractional transportation problem is formulated here. We take into account the parameters as cost, supply and demand are interval valued that involved in the proposed model, so we treat the model as a multi-objective linear fractional interval transportation problem. To solve the formulated model, we first convert it into a deterministic form using a new transformation technique and then apply fuzzy programming to solve it. The applicability of our proposed method is shown by considering two numerical examples. At last, conclusions and future research directions regarding our study is included.展开更多
Purpose–The nose length is the key design parameter affecting the aerodynamic performance of high-speed maglev train,and the horizontal profile has a significant impact on the aerodynamic lift of the leading and trai...Purpose–The nose length is the key design parameter affecting the aerodynamic performance of high-speed maglev train,and the horizontal profile has a significant impact on the aerodynamic lift of the leading and trailing cars Hence,the study analyzes aerodynamic parameters with multi-objective optimization design.Design/methodology/approach–The nose of normal temperature and normal conduction high-speed maglev train is divided into streamlined part and equipment cabin according to its geometric characteristics.Then the modified vehicle modeling function(VMF)parameterization method and surface discretization method are adopted for the parametric design of the nose.For the 12 key design parameters extracted,combined with computational fluid dynamics(CFD),support vector machine(SVR)model and multi-objective particle swarm optimization(MPSO)algorithm,the multi-objective aerodynamic optimization design of highspeed maglev train nose and the sensitivity analysis of design parameters are carried out with aerodynamic drag coefficient of the whole vehicle and the aerodynamic lift coefficient of the trailing car as the optimization objectives and the aerodynamic lift coefficient of the leading car as the constraint.The engineering improvement and wind tunnel test verification of the optimized shape are done.Findings–Results show that the parametric design method can use less design parameters to describe the nose shape of high-speed maglev train.The prediction accuracy of the SVR model with the reduced amount of calculation and improved optimization efficiency meets the design requirements.Originality/value–Compared with the original shape,the aerodynamic drag coefficient of the whole vehicle is reduced by 19.2%,and the aerodynamic lift coefficients of the leading and trailing cars are reduced by 24.8 and 51.3%,respectively,after adopting the optimized shape modified according to engineering design requirements.展开更多
Parameter optimization integrating operation parameters and structure parameters for the purpose of high permeate flux,high productivity and low exergy consumption of direct contact membrane distillation (DCMD) proces...Parameter optimization integrating operation parameters and structure parameters for the purpose of high permeate flux,high productivity and low exergy consumption of direct contact membrane distillation (DCMD) process was conducted based on Taguchi experimental design. L16(45) orthogonal experiments were carried out with feed inlet temperature,permeate stream inlet temperature,flow rate,module packing density and length-diameter ratio as optimization parameters and with permeate flux,water productivity per unit volume of module and water production per unit exergy loss separately as optimization objectives. By using range analysis method,the dominance degree of the various influencing factors for the three objectives was analyzed and the optimum condition was obtained for the three objectives separately. Furthermore,the multi-objectives optimization was performed based on a weight grade method. The combined optimum conditions are feed inlet temperature 75℃,packing density 30% ,length-diameter ratio 10,permeate stream inlet temperature 30 ℃ and flow rate 25 L/h,which is in order of their dominance degree,and the validity of the optimization scheme was confirmed.展开更多
Q345D high-quality low-carbon steel has been extensively employed in structures with stringent weld- ing quality requirements. A multi-objective optimization of welding stress and deformation was presented to design r...Q345D high-quality low-carbon steel has been extensively employed in structures with stringent weld- ing quality requirements. A multi-objective optimization of welding stress and deformation was presented to design reasonable values of gas metal arc welding parameters and sequences of Q345D T-joints. The optimized factors included continuous variables （welding current （I）, welding voltage （U） ahd welding speed （V）） and discrete variables （welding sequence （S） and welding direc- tion （D））. The concepts of the pointer and stack in Visual Basic （VB） and the interpolation method were introduced to optimize the variables. The optimization objectives included the different combina- tions of the angular distortion and transverse welding stress along the transverse and longitudinal dis- tributions. Based on the design of experiments （DOE） and the polynomial regression （PR） model, the finite element （FE） results of the T-joint were used to establish the mathematical models. The Pareto front and the compromise solutions were obtained by using a multi-objective particle swarm optimization （MOPSO） algorithm. The optimal results were validated by the corresponding results of the FE method, and the error between the FE results and the two-objective results as well as that be-tween the FE results and the three-objective optimization results were less than 17.2% and 21.5%, respectively. The influence and setting regularity of different factors were discussed according to the compromise solutions.展开更多
Recently, the single-shaft series-parallel powertrain of Plug-in Hybrid Electric Bus （PHEB） has become one of the most popu- lar powertrains due to its alterable operating modes, excellent fuel economy and strong ad...Recently, the single-shaft series-parallel powertrain of Plug-in Hybrid Electric Bus （PHEB） has become one of the most popu- lar powertrains due to its alterable operating modes, excellent fuel economy and strong adaptability for driving cycles. Never- theless, for configuring the PHEB with single-shaft series-parallel powertrain in the development stage, it still faces greater challenge than other configurations when choosing and matching the main component parameters. Motivated by this issue, a comprehensive multi-objectives optimization strategy based on Genetic Algorithm （GA） is developed for the PHEB with the typical powertrain. First, considering repeatability and regularity of bus route, the methods of off-line data processing and mathematical statistics are adopted, to obtain a representative driving cycle, which could well reflect the general characteristic of the real-world bus route. Then, the economical optimization objective is defined, which is consist of manufacturing costs of the key components and energy consumption, and combined with the dynamical optimization objective, a multi-objective op- timization function is put forward. Meanwhile, GA algorithm is used to optimize the parameters, for the optimal components combination of the novel series-parallel powertrain. Finally, a comparison with the prototype is carried out to verify the per- formance of the optimized powertrain along driving cycles. Simulation results indicate that the parameters of powertrain com- ponents obtained by the proposed comprehensive multi-objectives optimization strategy might get better fuel economy, meanwhile ensure the dynamic performance of PHEB. In contrast to the original, the costs declined by 18%. Hence, the strat- egy would provide a theoretical guidance on parameter selection for PHEB manufacturers.展开更多
We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of pa...We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved,it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives:(1) maximizing the Fisher information, improving the parameter estimation precision, and(2)minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ε-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.展开更多
In order to obtain a new-type short cylindrical cup-shaped flexspline that can be applied to space mechanisms,the APDL language of ANSYS software was employed to develop a parameterized equivalent contact model betwee...In order to obtain a new-type short cylindrical cup-shaped flexspline that can be applied to space mechanisms,the APDL language of ANSYS software was employed to develop a parameterized equivalent contact model between a flexspline and a wave generator. The validity of the parameterized equivalent contact model was verified by comparing the results of the analytic value of the contact model and the value calculated by the theoretical formula. The curvilinear trend of stress was obtained by changing the structural parameter of the flexspline. Based on the curvilinear trend of stress,multi-objective optimizations of key structural parameters were achieved. Flexspline,wave generator,and circular spline of a new 32-type short cylindrical cup-shaped harmonic reducer were designed and manufactured. A performance test bench to carry out tests on the harmonic reducer was designed. Contrast experiments were implemented to determine the efficiency of the new 32-type short cylindrical cup-shaped harmonic reducer and the conventional 32-type harmonic reducer under different conditions. The experimental results reveal that there is approximately equality in terms of efficiency between the new 32-type short cylindrical cup-shaped harmonic reducer and the conventional 32-type harmonic reducer. The volume of the flexspline of the new 32-type short cylindrical cup-shaped harmonic reducer is reduced by approximately 30% through multi-objective optimization. When the new 32-type short cylindrical cup-shaped harmonic reducer is used on the wheel of a rover prototype,the mass of the wheel hub is decreased by 0.42 kg. Test analysis of wheel motion verifies that the new 32-type short cylindrical cup-shaped harmonic reducer can meet the requirements regarding bearing capacity and efficiency.展开更多
This paper proposes an inverse method for improving the prediction of tunnel displacements during adjacent excavation.In this framework,staged data assimilation and parameter identification are conducted using the mul...This paper proposes an inverse method for improving the prediction of tunnel displacements during adjacent excavation.In this framework,staged data assimilation and parameter identification are conducted using the multi-objective particle swarm optimization algorithm.Recent monitoring data are assumed to be more informative and assigned more weights in the multi-objective optimization to improve the prediction accuracy.Then,an empirical formula is applied to correct the time effect of tunnel displacement.The Kriging method is introduced to surrogate the finite element model to reduce computational cost.The proposed framework is verified using a typical staged“excavation nearing tunnel”case.The predictions using the updated parameters are in good agreement with the measurements.The identified values of underlying soil parameters are within the typical ranges for the unloading condition.The updated time effect indicates that tunnel displacements may develop excessively in the three months after the region S1-B is excavated to the bottom.The maximum vertical tunnel displacement may increase from the currently measured 12 mm to the calculated 26 mm if the later construction is suspended long enough.Subsequent constructions need to be timely conducted to restrain the time effect and control tunnel displacements.展开更多
In order to solve the problems of uneven stubble,low cutting efficiency and frequent breaking and blocking in the cutting and conveying links of ramie combine harvester,a reciprocating double movable blades cutter and...In order to solve the problems of uneven stubble,low cutting efficiency and frequent breaking and blocking in the cutting and conveying links of ramie combine harvester,a reciprocating double movable blades cutter and a double-layer chain conveyor were designed,and the operating parameter test and optimization were carried out by using the central combination test design theory,with the emphasis on the influence of the forward speed,the cutting speed of the cutter and the conveying speed of the chain on the cutting efficiency,the failure rate and the conveying rate,and the multi-objective optimization was carried out based on these response indicators.Firstly,the structure and operating parameters of the cutting-conveying mechanism of ramie combine were studied.Then,the experiment was designed by the quadratic orthogonal rotation combination test method,and the data is processed by Design-Expert.The regression mathematical model of cutting efficiency,failure rate and conveying rate was established and variance analysis was carried out.By analyzing the effect of interaction of various factors on cutting efficiency,failure rate and conveying rate by response surface methodology,and performing multi-objective optimization on the regression model according to the importance of the optimization target,the optimal combination of the operating parameters of the cutting-conveying parts of the ramie combine harvester was obtained:when the forward speed was 0.85 m/s,the cutting speed was 1.40 m/s,and the chain conveying speed was 1.33 m/s,the cutting efficiency and conveying rate were the maximum and the failure rate was the minimum,with the values of 44.36 plants/s,93.60%and 4.16%,respectively.The optimized parameters were verified in the field on the ramie combine harvester.In the field test,the cutting efficiency,conveying rate,and failure rate were 43.80 plants/s,92.45%,and 4.52%,respectively,and the relative errors with the optimized values were 1.3%,1.2%,and 8.7%,respectively,which was relatively consistent.展开更多
In the present,most of domestic reed harvesters are still in the research and prototype stage,and there is not yet a model with mature technology,strong versatility and mass production.Some modified reed harvesters us...In the present,most of domestic reed harvesters are still in the research and prototype stage,and there is not yet a model with mature technology,strong versatility and mass production.Some modified reed harvesters used in some places can partially solve the reed harvesting problem,but there are problems such as small cutting width,unstable harvesting quality and low operational efficiency that need further improvement.In the study,a reed harvester was designed to integrate with the cutting and conveying.The key components of reed harvester were analyzed to determine the working parameters of the upper stalk-guiding device,the reciprocating double-acting cutter and the three-layer chain conveyor.Then,a quadratic orthogonal rotation combination test was designed to process the data by Design-Expert,where the failure rate,cutting efficiency and conveying rate were taken as the response indexes.An analysis was also made to explore the effects of forward speed,cutting speed,and chain conveying speed on the response index of the reed harvester.A regression mathematical model was established for the response indexes.The response surface method was then selected to implement the multi-objective optimization of the regression model.The results demonstrated that an optimal combination of operation parameters was achieved as follows:the forward speed was 0.85 m/s,the cutting speed was 1.40 m/s,and the chain conveying speed was 1.33 m/s,where the failure rate was 4.17%,the cutting efficiency was 44.21 plants/s,and the conveying rate was 93.60%.The optimized parameters were verified in the field on the reed harvester.In the field test,failure rate,cutting efficiency,and conveying rate were 4.38%,43.82 plants/s,and 92.55%,respectively.The relative errors with the optimized values were 9.8%,5.0%,and 1.1%,respectively.The results of the study provide a theoretical basis for the control of operating parameters and improved design of reed harvesting implements.展开更多
With shrinking technology,the increase in variability of process,voltage,and temperature(PVT) parameters significantly impacts the yield analysis and optimization for chip designs.Previous yield estimation algorithms ...With shrinking technology,the increase in variability of process,voltage,and temperature(PVT) parameters significantly impacts the yield analysis and optimization for chip designs.Previous yield estimation algorithms have been limited to predicting either timing or power yield.However,neglecting the correlation between power and delay will result in significant yield loss.Most of these approaches also suffer from high computational complexity and long runtime.We suggest a novel bi-objective optimization framework based on Chebyshev affine arithmetic(CAA) and the adaptive weighted sum(AWS) method.Both power and timing yield are set as objective functions in this framework.The two objectives are optimized simultaneously to maintain the correlation between them.The proposed method first predicts the guaranteed probability bounds for leakage and delay distributions under the assumption of arbitrary correlations.Then a power-delay bi-objective optimization model is formulated by computation of cumulative distribution function(CDF) bounds.Finally,the AWS method is applied for power-delay optimization to generate a well-distributed set of Pareto-optimal solutions.Experimental results on ISCAS benchmark circuits show that the proposed bi-objective framework is capable of providing sufficient trade-off information between power and timing yield.展开更多
基金financially supported by the National Key Research and Development Program of China(Grant No.2016YFB0701204)
文摘Multi-objective optimization has been increasingly applied in engineering where optimal decisions need to be made in the presence of trade-offs between two or more objectives. Minimizing the volume of shrinkage porosity, while reducing the secondary dendritic arm spacing of a wheel casting during low-pressure die casting(LPDC) process, was taken as an example of such problem. A commercial simulation software Pro CASTTM was applied to simulate the filling and solidification processes. Additionally, a program for integrating the optimization algorithm with numerical simulation was developed based on SiPESC. By setting pouring temperature and filling pressure as design variables, shrinkage porosity and secondary dendritic arm spacing as objective variables, the multi-objective optimization of minimum volume of shrinkage porosity and secondary dendritic arm spacing was achieved. The optimal combination of AZ91 D wheel casting was: pouring temperature 689 °C and filling pressure 6.5 kPa. The predicted values decreased from 4.1% to 2.1% for shrinkage porosity, and 88.5 μm to 81.2 μm for the secondary dendritic arm spacing. The optimal results proved the feasibility of the developed program in multi-objective optimization.
文摘In this paper, we present an algorithm to solve the inequality constrained multi-objective programming (MP) by using a penalty function with objective parameters and constraint penalty parameter. First, the penalty function with objective parameters and constraint penalty parameter for MP and the corresponding unconstraint penalty optimization problem (UPOP) is defined. Under some conditions, a Pareto efficient solution (or a weakly-efficient solution) to UPOP is proved to be a Pareto efficient solution (or a weakly-efficient solution) to MP. The penalty function is proved to be exact under a stable condition. Then, we design an algorithm to solve MP and prove its convergence. Finally, numerical examples show that the algorithm may help decision makers to find a satisfactory solution to MP.
文摘This paper presents a modified method to solve multi-objective nonlinear programming problems with fuzzy parameters in its objective functions and these fuzzy parameters are characterized by fuzzy numbers. The modified method is based on normalized trade-off weights. The obtained stability set corresponding to α-Pareto optimal solution, using our method, is investigated. Moreover, an algorithm for obtaining any subset of the parametric space which has the same corresponding α-Pareto optimal solution is presented. Finally, a numerical example to illustrate our method is also given.
文摘To enhance the output torque and minimize the torque ripple of coaxial magnetic gear(CMG),a novel auxiliary flux modulator CMG with unequal magnetic poles is proposed.This design incorporates an inner rotor with an asymmetric sector and a trapezoidal combined N-S pole structure,featuring Halbach arrays for the arrangement of permanent magnets(PMs).The outer rotor PMs adopt a Spoke-type configuration.To optimize the CMG for high output torque and low torque ripple,a sensitivity analysis is conducted to identify key size parameters that significantly influence the optimization objectives.Based on the sensitivity hierarchy of these parameters,a multi-objective optimization analysis is performed using a genetic algorithm(GA)to determine the optimal structural parameter values of the CMG.In addition,a coaxial magnetic gear(CMG)topology with 4 inner and 17 outer pole pairs is adopted,and the parametric model is established.Finally,the electromagnetic properties of the CMG are evaluated using the finite element method.The results indicate a remarkable reduction in torque ripple,specifically by 46.15%.
基金supported by the Hunan Provincial Natural Science Foundation of China(No.2023JJ40686).
文摘Enhancing the adaptability of Unmanned Aerial Vehicle(UAV)swarm control models to cope with different complex working scenarios is an important issue in this research field.To achieve this goal,control model with tunable parameters is a widely adopted approach.In this article,an improved UAV swarm control model with tunable parameters namely Multi-Objective O-Flocking(MO O-Flocking)is proposed.The MO O-Flocking model is a combination of a multi rule control system and a virtual-physical-law based control model with tunable parameters.To achieve multi-objective parameter tuning,a multi-objective parameter tuning method namely Improved Strength Pareto Evolutionary Algorithm 2(ISPEA2)is designed.Simulation experiment scenarios include six target orientation scenarios with different kinds of objectives.Experimental results show that both the ISPEA2 algorithm and MO O-Flocking control model have good performance in their experiment scenarios.
基金supported by the Natural Science Foundation of Hebei Province,China (No.E2014501077)Natural Science Foundation of China (No.51275345)
文摘To investigate cutting performance in the helical milling of carbon fiber reinforced polymer(CFRP),experiments were conducted with unidirectional laminates.The results show that the influence of cutting parameters is very significant in the helical milling process. The axial force increases with the increase of cutting speed, which is below 95 m/min; otherwise, the axial force decreases with the increase of cutting speed. The resultant force always increases when cutting speed increases; with the increase of tangential and axial feed rates, cutting forces increase gradually. In addition, damage rings can appear in certain regions of the entry edges; therefore, the relationship between machining performance(cutting forces and holemaking quality) and cutting parameters is established using the nonlinear fitting methodology. Thus, three cutting parameters in the helical milling of CFRP, under the steady state, are optimized based on the multi-objective genetic algorithm, including material removal rate and machining performance. Finally, experiments were carried out to prove the validity of optimized cutting parameters.
基金Supported by National Hi-tech Research and Development Program of China(863 Program,Grant No.2014AA041503)National Natural Science Foundation of China(Key Program,Grant No.51235003)
文摘As the manufacturing industry is facing increasingly serious environmental problems, because of which carbon tax policies are being implemented, choosing the optimum cutting parameters during the machining process is crucial for automobile panel dies in order to achieve synergistic minimization of the environment impact, product quality, and processing efficiency. This paper presents a processing task-based evaluation method to optimize the cutting parameters, considering the trade-off among carbon emissions, surface roughness, and processing time. Three objective models and their relationships with the cutting parameters were obtained through input–output, response surface, and theoretical analyses, respectively. Examples of cylindrical turning were applied to achieve a central composite design(CCD), and relative validation experiments were applied to evaluate the proposed method. The experiments were conducted on the CAK50135 di lathe cutting of AISI 1045 steel, and NSGA-Ⅱ was used to obtain the Pareto fronts of the three objectives. Based on the TOPSIS method, the Pareto solution set was ranked to find the optimal solution to evaluate and select the optimal cutting parameters. An S/N ratio analysis and contour plots were applied to analyze the influence of each decision variable on the optimization objective. Finally, the changing rules of a single factor for each objective were analyzed. The results demonstrate that the proposed method is effective in finding the trade-off among the three objectives and obtaining reasonable application ranges of the cutting parameters from Pareto fronts.
基金the National Key R&D Program of China(Grant No.2018YFB1501804)the National Natural Science Funds for Excellent Young Scholars of China(Grant No.51822406)+2 种基金the Sichuan Science and Technology Program(2021YJ0389)the Program of Introducing Talents of Discipline to Chinese Universities(111 Plan)(Grant No.B17045)the Beijing Outstanding Young Scientist Program(Grant No.BJJWZYJH01201911414038)。
文摘A geothermal demonstration exploitation area will be established in the Enhanced Geothermal System of the Qiabuqia field, Gonghe Basin, Qinghai–Xizang Plateau in China. Selection of operational parameters for geothermal field extraction is thus of great significance to realize the best production performance. A novel integrated method of finite element and multi-objective optimization has been employed to obtain the optimal scheme for thermal extraction from the Gonghe Basin. A thermal-hydraulic-mechanical coupling model(THM) is established to analyze the thermal performance. From this it has been found that there exists a contraction among different heat extraction indexes. Parametric study indicates that injection mass rate(Q_(in)) is the most sensitive parameter to the heat extraction, followed by well spacing(WS) and injection temperature(T_(in)). The least sensitive parameter is production pressure(p_(out)). The optimal combination of operational parameters acquired is such that(T_(in), p_(out), Q_(in), WS) equals(72.72°C, 30.56 MPa, 18.32 kg/s, 327.82 m). Results indicate that the maximum electrical power is 1.41 MW for the optimal case over 20 years. The thermal break has been relieved and the pressure difference reduced by 8 MPa compared with the base case. The optimal case would extract 50% more energy than that of a previous case and the outcome will provide a remarkable reference for the construction of Gonghe project.
基金financially supported by the Fundamental Research Funds for the Central Universities (No.FRF-MP20-08)。
文摘To deal with the increasing demand for low-volume customization of the mechanical properties of cold-rolled products, a two-way control method based on mechanical property prediction and process parameter optimization(PPO) has become an effective solution. Aiming at the multi-objective quality control problem of a company's cold-rolled products, based on industrial production data, we proposed a process parameter design and optimization method that combined multi-objective quality prediction and PPO. This method used the multi-output support vector regression(MSVR) method to simultaneously predict multiple quality indices. The MSVR prediction model was used as the effect verification model of the PPO results. It performed multi-process parameter collaborative design and realized the optimization of production process parameters for customized multi-objective quality requirements. The experimental results showed that, compared with the traditional single-objective quality prediction model based on support vector regression(SVR), the multi-objective prediction model could better take into account the coupling effect between process parameters and quality index, the MSVR model prediction accuracy was higher than that of the SVR, and the optimized process parameters were more capable and reflected the influence of metallurgical mechanism on the quality index,which were more in line with actual production process requirements.
文摘This paper studies a time-variant multi-objective linear fractional transportation problem. In reality, transported goods should reach in destinations within a specific time. Considering the importance of time, a time-variant multi-objective linear fractional transportation problem is formulated here. We take into account the parameters as cost, supply and demand are interval valued that involved in the proposed model, so we treat the model as a multi-objective linear fractional interval transportation problem. To solve the formulated model, we first convert it into a deterministic form using a new transformation technique and then apply fuzzy programming to solve it. The applicability of our proposed method is shown by considering two numerical examples. At last, conclusions and future research directions regarding our study is included.
文摘Purpose–The nose length is the key design parameter affecting the aerodynamic performance of high-speed maglev train,and the horizontal profile has a significant impact on the aerodynamic lift of the leading and trailing cars Hence,the study analyzes aerodynamic parameters with multi-objective optimization design.Design/methodology/approach–The nose of normal temperature and normal conduction high-speed maglev train is divided into streamlined part and equipment cabin according to its geometric characteristics.Then the modified vehicle modeling function(VMF)parameterization method and surface discretization method are adopted for the parametric design of the nose.For the 12 key design parameters extracted,combined with computational fluid dynamics(CFD),support vector machine(SVR)model and multi-objective particle swarm optimization(MPSO)algorithm,the multi-objective aerodynamic optimization design of highspeed maglev train nose and the sensitivity analysis of design parameters are carried out with aerodynamic drag coefficient of the whole vehicle and the aerodynamic lift coefficient of the trailing car as the optimization objectives and the aerodynamic lift coefficient of the leading car as the constraint.The engineering improvement and wind tunnel test verification of the optimized shape are done.Findings–Results show that the parametric design method can use less design parameters to describe the nose shape of high-speed maglev train.The prediction accuracy of the SVR model with the reduced amount of calculation and improved optimization efficiency meets the design requirements.Originality/value–Compared with the original shape,the aerodynamic drag coefficient of the whole vehicle is reduced by 19.2%,and the aerodynamic lift coefficients of the leading and trailing cars are reduced by 24.8 and 51.3%,respectively,after adopting the optimized shape modified according to engineering design requirements.
文摘Parameter optimization integrating operation parameters and structure parameters for the purpose of high permeate flux,high productivity and low exergy consumption of direct contact membrane distillation (DCMD) process was conducted based on Taguchi experimental design. L16(45) orthogonal experiments were carried out with feed inlet temperature,permeate stream inlet temperature,flow rate,module packing density and length-diameter ratio as optimization parameters and with permeate flux,water productivity per unit volume of module and water production per unit exergy loss separately as optimization objectives. By using range analysis method,the dominance degree of the various influencing factors for the three objectives was analyzed and the optimum condition was obtained for the three objectives separately. Furthermore,the multi-objectives optimization was performed based on a weight grade method. The combined optimum conditions are feed inlet temperature 75℃,packing density 30% ,length-diameter ratio 10,permeate stream inlet temperature 30 ℃ and flow rate 25 L/h,which is in order of their dominance degree,and the validity of the optimization scheme was confirmed.
基金financially sponsored by National Natural Science Foundation of China(No.50975121)Changchun Science and Technology Plan Projects(No.10KZ03)the Plan for Scientific and Technology Development of Jilin Province(No.20150520106JH)
文摘Q345D high-quality low-carbon steel has been extensively employed in structures with stringent weld- ing quality requirements. A multi-objective optimization of welding stress and deformation was presented to design reasonable values of gas metal arc welding parameters and sequences of Q345D T-joints. The optimized factors included continuous variables （welding current （I）, welding voltage （U） ahd welding speed （V）） and discrete variables （welding sequence （S） and welding direc- tion （D））. The concepts of the pointer and stack in Visual Basic （VB） and the interpolation method were introduced to optimize the variables. The optimization objectives included the different combina- tions of the angular distortion and transverse welding stress along the transverse and longitudinal dis- tributions. Based on the design of experiments （DOE） and the polynomial regression （PR） model, the finite element （FE） results of the T-joint were used to establish the mathematical models. The Pareto front and the compromise solutions were obtained by using a multi-objective particle swarm optimization （MOPSO） algorithm. The optimal results were validated by the corresponding results of the FE method, and the error between the FE results and the two-objective results as well as that be-tween the FE results and the three-objective optimization results were less than 17.2% and 21.5%, respectively. The influence and setting regularity of different factors were discussed according to the compromise solutions.
基金supported by the National Key Science and Technology Projects(Grant No.2014ZX04002041)
文摘Recently, the single-shaft series-parallel powertrain of Plug-in Hybrid Electric Bus （PHEB） has become one of the most popu- lar powertrains due to its alterable operating modes, excellent fuel economy and strong adaptability for driving cycles. Never- theless, for configuring the PHEB with single-shaft series-parallel powertrain in the development stage, it still faces greater challenge than other configurations when choosing and matching the main component parameters. Motivated by this issue, a comprehensive multi-objectives optimization strategy based on Genetic Algorithm （GA） is developed for the PHEB with the typical powertrain. First, considering repeatability and regularity of bus route, the methods of off-line data processing and mathematical statistics are adopted, to obtain a representative driving cycle, which could well reflect the general characteristic of the real-world bus route. Then, the economical optimization objective is defined, which is consist of manufacturing costs of the key components and energy consumption, and combined with the dynamical optimization objective, a multi-objective op- timization function is put forward. Meanwhile, GA algorithm is used to optimize the parameters, for the optimal components combination of the novel series-parallel powertrain. Finally, a comparison with the prototype is carried out to verify the per- formance of the optimized powertrain along driving cycles. Simulation results indicate that the parameters of powertrain com- ponents obtained by the proposed comprehensive multi-objectives optimization strategy might get better fuel economy, meanwhile ensure the dynamic performance of PHEB. In contrast to the original, the costs declined by 18%. Hence, the strat- egy would provide a theoretical guidance on parameter selection for PHEB manufacturers.
基金supported by the National Natural Science Foundation of China(Grant No.11404113)the Guangzhou Key Laboratory of Brain Computer Interaction and Applications(Grant No.201509010006)
文摘We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved,it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives:(1) maximizing the Fisher information, improving the parameter estimation precision, and(2)minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ε-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.
基金Project(2010DFR70270) supported by the International Science and Technology Cooperation Project with RussiaProjects(50975059,61005080) supported by the National Natural Science Foundation of China+2 种基金Project(B07018) supported by "111" Program of ChinaProject(SKLRS200801A02) supported by the Foundation of State Key Laboratory of Robotics and System (Harbin Institute of Technology),ChinaProject(HIT2009061) supported by the Key Subject Laboratory Open Fund of China
文摘In order to obtain a new-type short cylindrical cup-shaped flexspline that can be applied to space mechanisms,the APDL language of ANSYS software was employed to develop a parameterized equivalent contact model between a flexspline and a wave generator. The validity of the parameterized equivalent contact model was verified by comparing the results of the analytic value of the contact model and the value calculated by the theoretical formula. The curvilinear trend of stress was obtained by changing the structural parameter of the flexspline. Based on the curvilinear trend of stress,multi-objective optimizations of key structural parameters were achieved. Flexspline,wave generator,and circular spline of a new 32-type short cylindrical cup-shaped harmonic reducer were designed and manufactured. A performance test bench to carry out tests on the harmonic reducer was designed. Contrast experiments were implemented to determine the efficiency of the new 32-type short cylindrical cup-shaped harmonic reducer and the conventional 32-type harmonic reducer under different conditions. The experimental results reveal that there is approximately equality in terms of efficiency between the new 32-type short cylindrical cup-shaped harmonic reducer and the conventional 32-type harmonic reducer. The volume of the flexspline of the new 32-type short cylindrical cup-shaped harmonic reducer is reduced by approximately 30% through multi-objective optimization. When the new 32-type short cylindrical cup-shaped harmonic reducer is used on the wheel of a rover prototype,the mass of the wheel hub is decreased by 0.42 kg. Test analysis of wheel motion verifies that the new 32-type short cylindrical cup-shaped harmonic reducer can meet the requirements regarding bearing capacity and efficiency.
基金supported by the National Key Research and Development Program of China(Grant Nos.2017YFE0119500 and 2016YFC0800200)National Natural Science Foundation of China(Grant Nos.51620105008,52078464,and U2006225)the program of the China Scholarships Scholarship Council(No.202006320256).
文摘This paper proposes an inverse method for improving the prediction of tunnel displacements during adjacent excavation.In this framework,staged data assimilation and parameter identification are conducted using the multi-objective particle swarm optimization algorithm.Recent monitoring data are assumed to be more informative and assigned more weights in the multi-objective optimization to improve the prediction accuracy.Then,an empirical formula is applied to correct the time effect of tunnel displacement.The Kriging method is introduced to surrogate the finite element model to reduce computational cost.The proposed framework is verified using a typical staged“excavation nearing tunnel”case.The predictions using the updated parameters are in good agreement with the measurements.The identified values of underlying soil parameters are within the typical ranges for the unloading condition.The updated time effect indicates that tunnel displacements may develop excessively in the three months after the region S1-B is excavated to the bottom.The maximum vertical tunnel displacement may increase from the currently measured 12 mm to the calculated 26 mm if the later construction is suspended long enough.Subsequent constructions need to be timely conducted to restrain the time effect and control tunnel displacements.
基金Theauthorsgreatly appreciate the careful and precise reviews by the anonymousreviewers and editors.This research was financially supported by the Fundamental Research Funds for Central Non-profit Scientific Institution(S201932)National Key R&D Program of China(2016YFD0701404)+1 种基金earmarked fund forChina Agriculture Research System(CARS-16-E20)the Agricultural Science and Technology Innovation Program of theChinese Academy of Agricultural Sciences(ASTIP,CAAS).
文摘In order to solve the problems of uneven stubble,low cutting efficiency and frequent breaking and blocking in the cutting and conveying links of ramie combine harvester,a reciprocating double movable blades cutter and a double-layer chain conveyor were designed,and the operating parameter test and optimization were carried out by using the central combination test design theory,with the emphasis on the influence of the forward speed,the cutting speed of the cutter and the conveying speed of the chain on the cutting efficiency,the failure rate and the conveying rate,and the multi-objective optimization was carried out based on these response indicators.Firstly,the structure and operating parameters of the cutting-conveying mechanism of ramie combine were studied.Then,the experiment was designed by the quadratic orthogonal rotation combination test method,and the data is processed by Design-Expert.The regression mathematical model of cutting efficiency,failure rate and conveying rate was established and variance analysis was carried out.By analyzing the effect of interaction of various factors on cutting efficiency,failure rate and conveying rate by response surface methodology,and performing multi-objective optimization on the regression model according to the importance of the optimization target,the optimal combination of the operating parameters of the cutting-conveying parts of the ramie combine harvester was obtained:when the forward speed was 0.85 m/s,the cutting speed was 1.40 m/s,and the chain conveying speed was 1.33 m/s,the cutting efficiency and conveying rate were the maximum and the failure rate was the minimum,with the values of 44.36 plants/s,93.60%and 4.16%,respectively.The optimized parameters were verified in the field on the ramie combine harvester.In the field test,the cutting efficiency,conveying rate,and failure rate were 43.80 plants/s,92.45%,and 4.52%,respectively,and the relative errors with the optimized values were 1.3%,1.2%,and 8.7%,respectively,which was relatively consistent.
基金supported by Special Funds for Jiangsu Provincial Science and Technology Planning Project(BE2019360)Central Non-profit Scientific Institution(S202111-01)the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences(ASTIP,CAAS).
文摘In the present,most of domestic reed harvesters are still in the research and prototype stage,and there is not yet a model with mature technology,strong versatility and mass production.Some modified reed harvesters used in some places can partially solve the reed harvesting problem,but there are problems such as small cutting width,unstable harvesting quality and low operational efficiency that need further improvement.In the study,a reed harvester was designed to integrate with the cutting and conveying.The key components of reed harvester were analyzed to determine the working parameters of the upper stalk-guiding device,the reciprocating double-acting cutter and the three-layer chain conveyor.Then,a quadratic orthogonal rotation combination test was designed to process the data by Design-Expert,where the failure rate,cutting efficiency and conveying rate were taken as the response indexes.An analysis was also made to explore the effects of forward speed,cutting speed,and chain conveying speed on the response index of the reed harvester.A regression mathematical model was established for the response indexes.The response surface method was then selected to implement the multi-objective optimization of the regression model.The results demonstrated that an optimal combination of operation parameters was achieved as follows:the forward speed was 0.85 m/s,the cutting speed was 1.40 m/s,and the chain conveying speed was 1.33 m/s,where the failure rate was 4.17%,the cutting efficiency was 44.21 plants/s,and the conveying rate was 93.60%.The optimized parameters were verified in the field on the reed harvester.In the field test,failure rate,cutting efficiency,and conveying rate were 4.38%,43.82 plants/s,and 92.55%,respectively.The relative errors with the optimized values were 9.8%,5.0%,and 1.1%,respectively.The results of the study provide a theoretical basis for the control of operating parameters and improved design of reed harvesting implements.
文摘With shrinking technology,the increase in variability of process,voltage,and temperature(PVT) parameters significantly impacts the yield analysis and optimization for chip designs.Previous yield estimation algorithms have been limited to predicting either timing or power yield.However,neglecting the correlation between power and delay will result in significant yield loss.Most of these approaches also suffer from high computational complexity and long runtime.We suggest a novel bi-objective optimization framework based on Chebyshev affine arithmetic(CAA) and the adaptive weighted sum(AWS) method.Both power and timing yield are set as objective functions in this framework.The two objectives are optimized simultaneously to maintain the correlation between them.The proposed method first predicts the guaranteed probability bounds for leakage and delay distributions under the assumption of arbitrary correlations.Then a power-delay bi-objective optimization model is formulated by computation of cumulative distribution function(CDF) bounds.Finally,the AWS method is applied for power-delay optimization to generate a well-distributed set of Pareto-optimal solutions.Experimental results on ISCAS benchmark circuits show that the proposed bi-objective framework is capable of providing sufficient trade-off information between power and timing yield.
